The European Union's Waste Electrical and Electronic Equipment legislation requires manufacturers to reduce the disposal waste of electronic products by reuse, recycling, and other forms of recovery. To enhance the possibilities and economic profitability of recycling, elimination of hazardous materials from the electrical and electronic equipments was proposed under the supplementary directive, the Restriction of the Use of Certain Hazardous Substances in Electrical and Electronic Equipment. This directive bans lead and other hazardous substances in electronics products by July 2006. However, a number of exemptions indicated in these legislations could impact different industry sectors and product categories. In this paper, the underlying basis of the legislation and the various exemptions are presented. The relevance and significance of the exemptions to the electronics industry is then analyzed and recommendations are given.

The European Parliament's Waste Electrical and Electronic Equipment legislation requires manufacturers to hear responsibility for the mandatory collection, reuse and recycling of electronics products. The Restriction of the use of Hazardous Substances in electrical and electronic equipment legislation mandates the substitution of lead and other hazardous substances in electronics products by July 2006. The lead-free legislation contains a number of exemptions. The impact of the lead-free legislation exemptions varies across different industry sectors and product categories.In this paper, we have outlined the underlying basis of the exemptions and analyzed the relevance and significance of these exemptions to the electronics industry. We then examined how various sectors of the electronics industry will he able to respond to the exemptions in their product development.

Diabetes Mellitus (DM) is a metabolic disorder where the body fails to produce the digestive hormone insulin, or the body’s ability to respond to insulin is limited. This situation leads to abnormal metabolism of carbohydrates and elevated blood sugar level. Type-1 diabetes (T1DM) is a condition arises mainly due to auto immunity disorder in which the immunity cells of the body mistakenly destroy the beta cells in the pancreas, which produce insulin. T1DM patients require to have proper control of their blood glucose level through proper medication, physical activities and continuous monitoring of blood glucose levels. A wide range of advanced wellbeing innovations, particularly computerized applications, have been growing quickly to assist individuals with dealing with their diabetes. Artificial Intelligence is a rapidly growing field, and its applications to diabetes research are becoming significantly more quickly. This paper is a review of six studies of existing neural networkbased models for the prediction of future blood glucose level in T1DM patients and describes some challenges to predict future blood glucose with the available data. These models include prediction of blood glucose level using Convolutional Neural Networks (CNN), Feedforward Neural Network (FNN), Recurrent Neural Network (RNN) implemented using Long Short Term Memory (LSTM), Convolutional Recurrent Neural Network (CRNN), Bidirectional LSTM (BiLSTM) and Dilated Recurrent Neural Networks (DRNN)

This paper gives an idea in regards with the impact of Artificial Intelligence in Agrarian Sector. As India is an Agrarian Country, our economy is uncommonly dependent upon the yielding of harvests and its most prominent effectiveness. Most of people in our country depends upon cultivation for their everyday requirements. The usage of Artificial Intelligence close by its capacity of learning can give an enormous impact on the country sector.AI development helps in distinctive sickness in plants, vermin and sad sustenance of residences. Man-created insight sensors can recognize and target weeds and subsequently pick which herbicide to apply inside the area. This assistants in lessened utilization of herbicides and cost save reserves. Various mechanical associations make drobots, which use PC vision and man-made awareness to screen what's more, unequivocally shower on weeds. This paper moreover discusses the new developments that opens the way to a Smart Agriculture .This paper gives an idea in regards with the impact of Artificial Intelligence in Agricultural Sector.

Artificial intelligence is the simulation of human intelligence processes by machine , it plays a crusial role in our day to day life. Artificial intelligence has possibly changed wellbeing to an extremely incredible degree. The execution of Artificial Intelligence has expanded in numerous areas including the Medical sector . Artificially intelligent computer systems are used extensively in medical science. The common application of AI in medical sector include diagnosing patients, end-to-end drug discovery and development, improving communication between physician and patient , transcribing medical documents ,such as prescriptions, and remotely treating patients. Man-made intelligence is the boundless branch worried about building savvy machine equipped for performing undertakings that require human knowledge. AI in medical sector improves so many benefits to the peoples and also the organizations . This study investigates the advantages and difficulties associated with AI involving in medical services . It also consider the future grow of Ai in medical sector and what are the remedies for the challenges.